System and method for ran power and environmental orchestration

ABSTRACT

A power and environmental orchestration (P&amp;EO) system uses network utilization condition information to implement scenarios that partially or fully reduce power requirements for radio access network (RAN) elements. A network device obtains power orchestration scenarios for a RAN and evaluates utilization data of multiple components of the RAN against the power orchestration scenarios. The network device determines that the utilization data meets a threshold for one of the power orchestration scenarios and applies the one of the power orchestration scenarios to reconfigure the RAN for reduced power consumption.

BACKGROUND

Development and design of radio access networks (RANs) present certainchallenges from a network-side perspective, including increased powerconsumption of RAN components. Typically, wireless cell sites, hubs, orother sites are completely turned on and consuming full power or theyare completely down and consuming none.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an exemplary network environment in which a Power andEnvironmental Orchestration (P&EO) system described herein may beimplemented;

FIG. 2A illustrates exemplary logical components of the wirelessstations of FIG. 1 according to one implementation;

FIG. 2B illustrates exemplary logical components of the radio units ofFIG. 2A according to one implementation;

FIG. 3 is a block diagram illustrating an exemplary implementation ofthe P&EO system of in a portion of the network environment of FIG. 1;

FIG. 4 is a block diagram illustrating an exemplary implementation ofthe P&EO system of in another portion of the network environment of FIG.1;

FIG. 5 is a flow diagram illustrating exemplary processes for optimizingpower consumption in a radio access network, according to animplementation described herein;

FIG. 6 is a diagram illustrating components of the P&EO predictionsystem of FIG. 1, according to an implementation described herein;

FIG. 7 is an illustration of an exemplary prediction table for the P&EOprediction system as described herein;

FIG. 8 is a flow diagram illustrating an exemplary process forgenerating power orchestration scenarios, according to an implementationdescribed herein; and

FIG. 9 is a block diagram illustrating exemplary components of a devicethat may correspond to one of the devices described herein.

DETAILED DESCRIPTION OF EXAMPLE EMBODIMENTS

The following detailed description refers to the accompanying drawings.The same reference numbers in different drawings may identify the sameor similar elements. Also, the following detailed description does notlimit the invention.

In current radio access networks (RANs), there is no way to gracefullyreduce power consumption during times of lower load. Various proposedsolutions generally entail a complete shutdown of some elements, butthere is no coordinated way of orchestrating the various componentsinvolved. Under normal operating conditions under a standard power grid,optimizing power consumption by RAN resources can reduce overall energyconsumption in a wireless network. When emergency backup power is beingused (e.g., in the event of a power failure), it would be beneficial toprovide optimized power consumption of RAN resources to ensure thatwireless access remains available to users.

According to implementations described herein, a Power and EnvironmentalOrchestration (P&EO) system may use various RAN and network utilizationcondition information, from power control and measurement elements, toimplement scenarios that partially or fully reduce power and coolingbased on controlled systems.

The P&EO system may be designed to work with a network functionvirtualization (NFV) environment and can run on a Virtualized ControllerPlatform (VCP). The P&EO system can ingest power usage information fromvarious devices in the site such as RU's (Radio Units), blades runningin the VCP itself, transport equipment, power and cooling equipment,etc. The P&EO system may also ingest utilization information fromvirtualized Base Band Units (vBBU), as well as other equipment.

Further, P&EO system may have functional control over RAN elements suchthat adjustments to their configurations can be actively implemented toreduce power loads based on certain power orchestration scenarios. Forexample, as the user load meets certain usage scenario thresholds, thescenario may be enacted to reduce the Effective Isotropic Radiated Power(EIRP) of a transmit antenna power, which in turn results in reducedpower consumption. Some units can be completely turned off. The coolingcan then be reduced to match the resulting reduction in generated heat.

FIG. 1 illustrates an exemplary environment 100 in which an embodimentof the P&EO system may be implemented. As illustrated, environment 100includes an access network 105, one or more edge networks 130, a corenetwork 150, and one or more data networks 160. Access network 105 mayinclude wireless stations 110-1 through 110-X (referred to collectivelyas wireless stations 110 and generally as wireless station 110).Environment 100 further includes a P&EO controller 170, aSelf-Organizing Network (SON) function 175, a P&EO prediction system180, and one or more UE devices 190.

The number, the type, and the arrangement of network devices and thenumber of UE devices 190 illustrated in FIG. 1 are exemplary. A networkdevice, a network element, or a network function (referred to hereinsimply as a network device) may be implemented according to one ormultiple network architectures, such as a client device, a serverdevice, a peer device, a proxy device, a cloud device, a virtualizedfunction, and/or another type of network architecture (e.g., SoftwareDefined Networking (SDN), virtual, logical, network slicing, etc.).Additionally, a network device may be implemented according to variouscomputing architectures, such as centralized, distributed, cloud (e.g.,elastic, public, private, etc.), edge, fog, and/or another type ofcomputing architecture.

Environment 100 includes communication links 120 between the networks,between the network devices, and between UE devices 190 and the networkdevices. Environment 100 may be implemented to include wired, optical,and/or wireless communication links 120 among the network devices andthe networks illustrated. A connection via a communication link 120 maybe direct or indirect. For example, an indirect connection may involvean intermediary device and/or an intermediary network not illustrated inFIG. 1. A direct connection may not involve an intermediary deviceand/or an intermediary network. The number and the arrangement ofcommunication links illustrated in environment 100 are exemplary.

Access network 105 may include one or multiple networks of one ormultiple types and technologies. For example, access network 105 mayinclude a Fifth Generation (5G) radio access network (RAN), FourthGeneration (4G) RAN, and/or another type of future generation RAN. Byway of further example, access network 105 may be implemented to includea 5G New Radio (5G NR) RAN, an Evolved UMTS Terrestrial Radio AccessNetwork (E-UTRAN) of a Long Term Evolution (LTE) network, anLTE-Advanced (LTE-A) network, and/or an LTE-A Pro network, and/oranother type of RAN (e.g., a legacy RAN). Access network 105 may furtherinclude other types of wireless networks, such as a WiFi network, aWorldwide Interoperability for Microwave Access (WiMAX) network, a localarea network (LAN), or another type of network that may provide anon-ramp to wireless stations 110 and/or core network 150.

Depending on the implementation, access network 105 may include one ormultiple types of wireless stations 110. For example, wireless station110 may include a next generation Node B (gNB) for a 5G NR RAN, anevolved Node B (eNB), an evolved Long Term Evolution (eLTE) eNB, a radionetwork controller (RNC), a remote radio head (RRH), a baseband unit(BBU), a small cell node (e.g., a picocell device, a femtocell device, amicrocell device, a home eNB, a repeater, etc.), or another type ofwireless node. According to various embodiments, access network 105 maybe implemented according to various wireless technologies (e.g., radioaccess technology (RAT), etc.), wireless standards, wirelessfrequencies/bands, and so forth. According to an implementation,wireless stations 110 may include a gNB with multiple distributedcomponents, such as a central unit (CU), a distributed unit (DU), aremote unit (RU or a remote radio unit (RRU)), or another type ofdistributed arrangement. As further discussed below, wireless stations110 (as part of access network 105) may be part of a Self-OrganizingNetwork (SON) that may be reconfigured by another component in networks105, 130, and/or 150.

Each wireless station 110 typically uses multiple carrier frequencies ina single instance. For example, a single wireless station 110 mayprovide coverage over an area referred to as a cell. A cell typicallyuses multiple carrier frequencies to meet capacity demands and provideguaranteed service quality within each cell. It is not cost effective todeploy all carrier frequencies on every cell that a wireless carriermanages in a particular area. A cell may be divided into one or moresectors, with each sector providing different areas of coverage that mayoverlap. A particular sector may also transmit and/or receive signals onone or more predefined carrier frequencies. The combination of a sectorand a particular carrier frequency may be referred to herein as a“sector carrier.”

Edge network 130 includes a platform that provides application servicesat the edge of a network, such as services for the P&EO system describedherein. For example, edge network 130 may be implemented as aMulti-access Edge Compute (MEC) platform. Edge network 130 may includenetwork devices located to provide geographic proximity to variousgroups of wireless stations 110. In some embodiments, components of edgenetwork 130 may be co-located with wireless stations 110 in RAN 105. Inother embodiments, wireless stations 110 may connect to edge network 130via wired (e.g., optical) backhaul links 120.

Edge network 130 may be implemented using one or multiple technologiesincluding, for example, network function virtualization (NFV), softwaredefined networking (SDN), cloud computing, or another type of networktechnology. Depending on the implementation, edge network 130 mayinclude, for example, virtualized network functions (VNFs), multi-access(MA) applications/services, and/or servers. Edge network 130 may alsoinclude other network devices that support its operation, such as, forexample, a network function virtualization orchestrator (NFVO), avirtualized infrastructure manager (VIM), an operations support system(OSS), a local domain name server (DNS), a virtual network functionmanager (VNFM), and/or other types of network devices and/or networkresources (e.g., storage devices, communication links, etc.).

Core network 150 may include one or multiple networks of one or multiplenetwork types and technologies. For example, core network 150 may beimplemented to include a next generation core (NGC) network for a 5Gnetwork, an Evolved Packet Core (EPC) of an LTE network, an LTE-Anetwork, an LTE-A Pro network, and/or a legacy core network. Dependingon the implementation, core network 150 may include various networkcomponents and devices 155, such as for example, a user plane function(UPF), an access and mobility management function (AMF), a sessionmanagement function (SMF), a unified data management (UDM) device orfunction, an authentication server function (AUSF), a network sliceselection function (NSSF), network data analytics function (NWDAF), andso forth. For purposes of illustration and description, network devices155 may include various types of network devices that may be resident incore network 150.

Core network 150 may manage communication sessions for UE devices 190.For example, core network 130 may establish an Internet Protocol (IP)connection between UE device 190 and a particular data network 160.Furthermore, core network 150 may enable UE device 190 to communicatewith an application server or another type of network device 165 locatedin a particular data network 160 using a communication method that doesnot require the establishment of an IP connection between UE device 190and data network 160, such as, for example, Data over Non-Access Stratum(DoNAS).

Data network 160 may include one or multiple networks. For example, datanetwork 160 may be implemented to include a service or anapplication-layer network, the Internet, an Internet Protocol MultimediaSubsystem (IMS) network, a Rich Communication Service (RCS) network, acloud network, a packet-switched network, or other type of network thathosts a user device application or service. Depending on theimplementation, data network 160 may include various network devicesthat provide various applications, services, or other type of userdevice assets (e.g., servers (e.g., web, application, cloud, etc.), massstorage devices, data center devices), and/or other types of networkservices pertaining to various network-related functions.

P&EO controller 170 may include one or more network devices configuredto implement the P&EO system. According to an implementation, P&EOcontroller 170 may monitor RAN utilization data and implement powerorchestration scenarios during periods of low use to reduce/optimizepower consumption by RAN components, while maintaining required levelsof service. According to an implementation, P&EO controller 170 may beincluded at a network edge, such as within access network 105 or edgenetwork 130. According to another implementation, P&EO controller 170may select an edge resource, from the multiple edge networks 130 and orwireless stations 110, to provide requested power optimization servicesand may instruct the edge devices to perform container provisioning andservice provisioning for the P&EO system. P&EO controller 170 isdescribed further in connection with, for example, FIGS. 3-5.

As further shown, core network 150 may include a SON function 175.Depending on the embodiment, SON function 175 may be implemented as oneor more network devices and/or software (e.g., a program). SON function175 may include logic for modifying operating parameters of accessnetwork 105, including those of wireless stations 110. As furtherexplained below, P&EO controller 170 may notify SON function 175 whenthresholds (e.g., one or more indicators of RAN utilization levels) fora power orchestration scenario have been met. SON function 175 maydetermine an optimal solution for a reduced power use configuration(e.g. EIRP, up or down tilt, or other applicable parameters) for thegiven scenario. According to an implementation, SON function 175 mayenact the reduced power use configuration by issuing commands towireless stations 110 and/or other components in access network 105. Inanother implementation, SON function 175 may direct P&EO controller 170to implement some or all of the configuration changes to enact thereduced power use configuration.

P&EO prediction system 180 may generate power orchestration scenarios350 that can be used by P&EO controller 170 to detect and initiatereduced power use configurations for devices in access network 105.According to an implementation, P&EO prediction system 180 may ingesthistorical network data and apply machine learning to predict conditionswhen wireless stations 110 or other network elements can implementreduced power use configurations.

UE devices 190 may each include a mobile device, such as wireless orcellular telephone device (e.g., a conventional cell phone with dataprocessing capabilities), a smart phone, a personal digital assistant(PDA) that can include a radiotelephone, etc. In another implementation,UE device 190 may include any type of mobile or fixed computer device orsystem, such as a personal computer (PC), a laptop, a tablet computer, anotebook, a netbook, a wearable computer (e.g., a wrist watch,eyeglasses, etc.), a game playing device, a music playing device, etc.In other implementations, UE devices 190 may be implemented as amachine-type communications (MTC) device, an Internet of Things (IoT)device, a machine-to-machine (M2M) device, etc., that includescommunication functionality, such as a home appliance device, a homemonitoring device, a camera, etc. UE devices 190 may connect to wirelessstations 110 in a wireless manner.

FIG. 2A illustrates exemplary logical components of wireless stations110 of FIG. 1 according to one implementation. Consistent with FIG. 1,wireless stations 110 is included in access network 105. Although accessnetwork 105 may include other wireless stations 110, they are not shownin FIG. 2A. Each of wireless station includes a central unit (CU) 202,distributed units (DUs) 204-1 through 204-M, and, for each DU 204, oneor more Radio Units (RUs) 206-1 through 206-N. RU 206 may also bereferred to as a remote radio head (RRH). For simplicity, other RUs arenot shown in FIG. 2A.

CUs 202 may control DUs 204 over a front haul interface. CUs 202 maymanage, for example, sharing access network 105, conveying user data,mobility, sessions, etc. For each CU 202, there may be multiple DUs 204that the CU 202 controls.

CU 202 may process upper layers 402 of the communication protocol stackfor wireless stations 110. CUs 202 may not necessarily be physicallylocated near DUs 204, and may be implemented as cloud computingelements, through network function virtualization (NFV) capabilities ofthe cloud. In one implementation, CU 202 communicates with components ofcore network 150 through S 1/NG interfaces and with other CUs 202through X2/XN interfaces.

DUs 204 may be controlled by CU 202. For each DU 204 in access network150, there is only one CU 202. However, each DU 204 may send signals tomultiple RUs 206 for transmission. DUs 204 may handle UE devicemobility, from DU to DU, from a wireless station 110 to another wirelessstation 110, from a cell to another cell, from a beam to another beam,etc. DUs 204 communicate with a CU 202 through an F1 interface, and mayprocess lower layers of a communication protocol stack for wirelessstation 110.

FIG. 2B illustrates exemplary logical components of the RUs 206 of FIG.2A according to one implementation. As shown, RU 206-1 may include radiocircuit (RC) 212-1 and antenna elements 214-1. RU 206-2 may includeradio circuit 212-2 and antenna elements 214-2. Depending on theimplementation, RU 206-1 and RU 206-2 may include additional, fewer,different, or differently arranged components than those illustrated inFIG. 2B.

RC 212 may receive signals from DU 206, process them, and send them toantenna elements 214 for transmission. Antenna elements 214 may receivethe signals and radiate the signals as a beam 216. In FIG. 2B, antennaelements 214-1 are shown as forming a beam 216-1 that reaches coveragearea 218-1 and, and antenna elements 214-2 are shown as forming beam216-2 that reach coverage area 218-2.

RUs 206 in FIG. 2B are capable of controlling beam shape, beam strength,and beam directions to balance traffic load over different bands. Forexample, assume that beam 216-1 and beam 216-2 cover the same area. DU204 may set a minimum transmit power level at RU 206-1 for which UEdevices in coverage area 218-1 may connect to wireless station 110through beam 216-1. If SON function 175 instructs CU 202 and thus DU 204to increase the minimum transmit power level for RU 206-1, the UEdevices 102 in coverage area 218-1 may no longer remain connected towireless station 110 via beam 216-1 (assuming that the signal strengthsare the same). In the scenario, the UE devices 102 may then connect towireless station 110 via beam 218-2 (which may occupy another frequencyband), assuming that minimum transmit power level for the correspondingRU 206-2 remains the same. Accordingly, by lowering or raising theminimum transmit power level at DUs 204, SON function 175 may decreaseor increase the traffic load at a particular band.

In another example, assume that beams 216-1 and 216-2 cover the samearea (i.e., 218-1 and 218-2 are the same) and that beam 216-1 carriesmore traffic than beam 216-2 by y % (e.g., 15%). If beams 216-1 and216-2 differ in direction by an angle X (e.g., 1 degree) beam 216-1(which may be determined by comparing the portion of beam 216-1 with atleast 3 DB power to the portion of beam 216-2 with at least 3 DB power),SON function 175 may instruct DU 204 (via CU 202) to tilt up beam 216-2,to better cover its area.

FIG. 3 is a block diagram illustrating an exemplary implementation ofthe P&EO system of in a portion 300 of network environment 100. As shownin FIG. 3, network portion 300 may include P&EO controller 170, SONfunction 175, a power supply 305, one or more air conditioning (A/C)units 310, intermediate equipment 315-1 through 315-X (referred tocollectively as “intermediate equipment 315”), radio equipment 320-1through 320-Y (referred to collectively as “radios 320”), a powercontrol bus 330, a data bus 340, and power orchestration scenarios 350.

Power supply 305 may include an emergency or permanent electrical powersource for equipment associated with a wireless station 110 or anothercomponent of access network 105. For example, a permanent power supplymay include a continuous alternating current (AC) power source.Alternatively, power supply 305 may include an emergency direct current(DC) power source, such as a generator or a battery that engages in theevent of a power failure, for example.

A/C unit 310 may include an environmental cooling system forintermediate equipment 315 and/or radio equipment 320 in access network105. A/C unit 310 may also include an environmental cooling system forsystems impacted by changes to loads in wireless stations 110, such asbackend systems in edge network 130 and/or core network 150.

Intermediate equipment 315 may include components such as routers andmultiplexers within access network 105. Intermediate equipment 315 maycorrespond to access network equipment located between core network 150and RU 206, for example. Radio equipment 320 may include one or moreradio components of wireless station 110, such as RU 206.

Power control bus 330 may include a communications channel to allow P&EOcontroller 170 to adjust power levels to devices in access network 105and/or other components in network portion 300.

Data bus 340 may include a message bus to exchange data betweencomponents in network portion 300. The data may include user demand andutilization data, as well as RAN and other data. The power utilizationis also collected either from the equipment itself or from clamp onpower meters (not shown), which may tie into data bus 340. Data bus 340may support, for example, a publish-subscribe (pub-sub) model. In a databus 340, such as a Pulsar bus or Kafka bus, a producer contributes astream of records to one or more topics. A consumer subscribes to theone or more topics, and selectively retrieves records of subscribedtopics for consumption. Data bus 340 may feed real-time open sourceremote procedure calls (e.g., gRPC), Simple Network Management Protocol(SNMP), or other data to P&EO controller 170.

Power orchestration scenarios 350 may include model for different accessnetwork 105 configurations that can be implemented to optimize networkequipment utilization and power consumption for given customer userates. For example, power orchestration scenarios 350 may identity timesand/or usage thresholds where the number of active sector carriers canbe reduced for certain wireless stations 110 while still providingrequired levels of service.

For example, assume the number of users served by a wireless station 110with twelve sector carriers falls to a low level during an off-peakperiod. When at full power, assume the wireless station 110 consumes 15kWh. Preferably, a power orchestration scenario 350 would permit thewireless station 110 to serve the active users during the off-peakperiod using only two sector carriers with significantly reduced power(e.g., 1 or 2 kWh) and a corresponding cooling adjustment. As describedfurther herein, power orchestration scenarios 350 may be modeled andadapted by applying artificial intelligence and/or machine learning tohistorical network data, such as data collected via data bus 340.

Although FIG. 3 illustrates one arrangement of an environment 300 for aP&EO system, in other implementations, environment 300 may contain fewercomponents, different components, differently-arranged components, oradditional components than depicted in FIG. 3. For example, in anotherimplementation, a network data analytics function (NWDAF) or anothercore network component may provide additional network utilization data.Thus, communications described above in connection with FIG. 3 may usedifferent communications interfaces to exchange data and provide powerorchestration scenarios 350 than described above. Alternatively, oradditionally, one or more components of environment 300 may perform oneor more other tasks described as being performed by one or more othercomponents of environment 300.

FIG. 4 is a block diagram illustrating an exemplary implementation ofthe P&EO system of in a virtualization platform 400 of the networkenvironment 100. As shown in FIG. 4, virtualization platform 400 mayinclude a virtualized controller platform (VCP) 410. Components of VCP410 may be included in core network 150 (e.g., network devices 155), anedge hub for access network 105, or edge network 130.

VCP 410 may include one or more physical computing resources, such a asprocessors, computer devices, etc., referred to as blades 412 in FIG. 4.Virtual network devices, referred to herein as network functionvirtualization (NFV) instances 416-1 through 416-Q, may be implementedon blades 412 under direction of a hypervisor 414 or another type ofvirtual machine monitor. In other implementations, NFV instances 416 maybe implemented using one or multiple virtualization technologies, suchas a hypervisor, a host, a container, a virtual machine (VM), a networkfunction virtualization (NFV) infrastructure, a network functionvirtualization orchestrator (NFVO), a virtual network function manager(VNFM), a virtualized infrastructure manager (VIM), a platform managerand/or other types of virtualization elements (e.g., virtual networkfunction (VNF), etc.), layers, hardware resources, operating systems,software resources, engines, etc.

According to an implementation, P&EO controller 170 may be implementedas one of NFV instances 416 within VCP 410. Other NFV instances 416 maycontrol forwarding of packets via to/from access network 105. Forexample, NFV instances 416 may be configured to support network slicesconfigured with different characteristics to support different types ofapplications and/or services, such as video streaming, massiveInternet-of-Things (IoT) traffic, autonomous driving, etc. NFV instances416 may also apply admission controls to direct wireless stations 110and/or other network devices in backhaul links 120 to admit, block,delay or redirect a requesting UE device 190 depending on slicecongestion levels and other factors. Thus, the usage and powerconsumption of blades 410 may be directly or indirectly related to thenumber of active NFV instances 416 executing on 410. Blades 410 mayreport power usage information to P&EO controller 170 via data bus 340,for example.

FIG. 4 illustrates exemplary components of virtualization platform 400.Depending on the implementation, virtualization platform 400 may includeadditional, fewer, different, or differently arranged components thanthose illustrated in FIG. 4.

FIG. 5 is a flow diagram illustrating exemplary processes 500 foroptimizing power consumption in a radio access network. In oneimplementation, process 500 may be performed by P&EO controller 170. Inanother implementation, process 500 may be performed by P&EO controller170 in conjunction with SON function 175 and/or another network devicein network environment 100.

Process 500 may include obtaining power orchestration scenarios (block510). For example, power orchestration scenarios 350 may be provided toP&EO controller 170 and/or generated by P&EO controller 170. The powerorchestration scenarios may include triggering thresholds and networkconfigurations to optimize power consumption for access network 105,particularly during periods of low utilization.

Process 500 may further include ingesting utilization data (block 520),evaluating the utilization data against the power orchestrationscenarios (block 530), and determining if a power orchestration scenariois met (block 540). For example, P&EO controller 170 may receiveutilization and power use information from devices (e.g., intermediateequipment 315, radio equipment 320, etc.) in access network 105 via databus 340. P&EO controller 170 may identify thresholds from powerorchestration scenarios 350 and determine if one or more thresholds aremet in the collected utilization and power use information.

If a power orchestration scenario is not met (block 540—No), process 500may return to process block 520 to continue to ingest utilization data.If a power orchestration scenario is met (block 540—Yes), process 500may include interfacing with a SON function to check for an alternatesolution (block 550) and determining if an alternate SON solution isavailable (block 560). For example, P&EO controller 170 may optionallyinterface with SON function 175 to confirm or change optimalreduced-power settings for access network 105. In one implementation,SON function 175 may verify that a particular power orchestrationscenario 350 identified by P&EO controller 170 is suitable forimplementation. In another implementation, SON function 175 may providean alternative reduced-power configuration for access network 105 oroverride a power orchestration scenario to maintain full power.

If an alternate SON solution is available (block 560—Yes), process 500may additionally include applying a power control template from the SONrecommendation (block 570). For example, SON function 175 may providecontrol information to P&EO controller 170 as to what the optimalreduced power settings are for access network 105. Alternatively, SONfunction 175 may determine that other network factors may precludeimplementation of reduced power settings.

If an alternate SON solution is not available (block 560—No), process500 additionally include applying the power orchestration scenario(block 580). For example, P&EO controller 170 may determine thatappropriate low-utilization thresholds are met for one or more wirelessstations 110 in access network 105 and that SON function 175 has notsupplied additional input (if applicable). P&EO controller 170 may thenimplement an appropriate power orchestration scenario 350 to optimizeuse of radio resources in wireless station 110 and reduce powerconsumption in access network 105. For example, a number of sectorcarriers for a wireless station 110 may be powered down while the powerlevel of the remaining sector carriers may be increased and antenna downtilt increased to control interference to other sites. Alternatively,P&EO controller 170 may determine that utilization levels needs toincrease above a threshold for one or more wireless stations 110 andthat SON function 175 has not supplied additional input (if applicable).Accordingly, P&EO controller 170 may implement an appropriate powerorchestration scenario 350 to increase use of radio resources inwireless station 110 to higher or full capacity.

FIG. 6. is a diagram illustrating P&EO prediction system 180 forgenerating/updating power consumption models, according to animplementation described herein. System 180 may include one or moremodeling functions 610 and a prediction engine 620. System 180 may beimplemented, for example, in one or more network devices 155 of corenetwork 150. In other implementations, system 180 may be implemented inone or more of edge networks 130 or in a distributed environment.

Modeling function 610 may receive utilization data 602, environmentalconditions 604, and power measurements 606 from network sources.Utilization parameters 602, for example, may be collected by one or moreOperations, Administration, and Maintenance (OAM) systems in networkenvironment 100 (e.g., in access network 105 and/or core network 150)and stored in a database where modeling function 610 may access thesedata elements to estimate/predict low utilization periods for possiblepower level savings based on various parameters, such as those listed inconnection with FIG. 7, as well as others that can be considered. Foreach wireless station 110, modeling function 610 may create a predictiveutilization model, such as prediction weight table 612, that predictsthe power savings vs. network performance cost trade off.

FIG. 7 provides a diagram illustrating a portion of a prediction weighttable 612 for a power orchestration scenario. Referring to FIG. 7,prediction weight table 612 may include one or more parameter identifierfields 705, one or more threshold fields 710, one or more weight factorfields 715, and a variety of entries 750 associated with each of fields705-715. In table 700, each set of rows may correspond to a separatethreshold input parameter. In one implementation, thresholds may applyto the resource usage and performance of each respective wirelessstation 110. That is, each wireless station 110 (or another networkelement) may have a table 700 that is fed into the prediction engine620.

Parameter identifier field 705 may include one or more measurableindicators of a wireless station 110 that may have an impact on networkpower consumption. Parameter identifier field 705 may include one or twoor more features in combination, that may be indicative of particularnetwork conditions where power consumption can be reduced. Features mayinclude, for example, a utilization percentage, a number of connectedusers (e.g., a number of radio resource control (RRC) connections,), aphysical resource block (PRB) utilization level, a transition timeinterval (TTI) utilization, a throughput level (e.g., burst userthroughput), Channel Quality Indicator (CQI) Received Signal StrengthIndication (RSSI) value, Timing Advance (TA) distance, mobility, etc.Each data element in parameter identifier field 705 maps to a particularthreshold in threshold field 710, which is mapped to power savingsweighting factor in weight factor field 715.

Threshold field 710 may include one or more thresholds for features incorresponding parameter identifier fields 705. Threshold field 710 mayinclude a numerical value, a percentage value, or another type of valuethat may indicate, for example, that a wireless station may beexperiencing low utilization.

Weight factor field 715 may include a weight factor for elements incorresponding parameter identifier fields 705. The weight factor may beindicative of the potential power savings associated with correspondingelement. The weight values in weight factor field 715 may have aninitial estimate but can be changed over time as various conditions orresults vary depending on the specific user patterns or other uniquefactors for a specific wireless station 110. Further, the feedback fromSON function 175 may alter thresholds dynamically as well. This approachcan be used to refine scenarios over time as actual realized powersavings vs. network performance results. Utilization in some scenariosmay be cyclical (i.e., time of day, commuter vs. work-at-home traffic,etc.). Thus required power levels can be predictable.

Although FIG. 7 shows exemplary information that may be provided inprediction model 612 for a wireless station 110, in otherimplementations, prediction model 612 may contain less, different,differently-arranged, or additional information than depicted in FIG. 7.For example, fields in prediction model 612 may be broken down by sectorcarrier and include time of day and other external data. Also,prediction model 612 may be replaced with a flat file structure withstrings of features and settings in place of designated fields.

Returning to FIG. 6, prediction engine 620 may receive prediction models612 and may create power orchestration scenarios 350 based on theprediction models 612. For example, prediction engine 620 may determinecombinations of wireless stations 110 that can support predictedconditions with lower-than-normal power for given periods. Predictionengine 620 may identify, for example, different combinations of sectorcarriers at different wireless stations that can be used to provide alow-power consumption scenario for periods of low RAN utilization.According to an implementation, prediction engine 620 may applyartificial intelligence to provide initial estimates based on trainingdata and provide updates as historical data is added to the data set.Power orchestration scenarios 350 may be provided to P&EO controller 170for implementation, as described above in connection with FIG. 3, forexample.

FIG. 8 is a flow diagram illustrating an exemplary process 800 forgenerating a power orchestration scenario the P&EO system. In oneimplementation, process 800 may be performed by prediction system 180.In another implementation, process 800 may be performed by P&EOprediction system 180 in conjunction with one or more other networkdevices in network environment 100, such as P&EO controller 170 and/orSON function 175.

Process 800 may include ingesting network utilization data (block 810),and estimating possible power level savings (block 820). For example,modeling function 610 of P&EO prediction system 180 may receive RANutilization data and other data from network elements. In oneimplementation, various network utilization data may be collected viaOAM systems that feed a local database accessible by modeling function610. In one aspect, modeling function 610 may normalize the data, removeoutliers, etc. Using different artificial intelligence and machinelearning processes, for example, modeling function 610 may access thestored data elements to estimate and/or predict possible power levelsavings based on the various parameters. According to an implementation,modeling function 610 may generate a prediction weight table 612 foreach wireless station 110.

Process 800 may further include generating a power orchestrationscenario (block 830), and providing the power orchestration scenario toa controller (block 840). For example, prediction engine 620 may receiveprediction models 612 from modeling function 610 and may create powerorchestration scenarios 350 based on the prediction models 612.Prediction engine 620 may forward the power orchestration scenarios 350to P&EO controller 170 for implementation. Additionally, as new networkutilization data is provided, modeling function 610 may provide updatedprediction models 612, which in turn may be used by prediction engine620 to updated power orchestration scenarios 350.

FIG. 9 is a block diagram illustrating exemplary components of a devicethat may correspond to one of the devices of FIGS. 1-8. Each of wirelessstation 110, network devices 155, P&EO controller 170, SON function 175,P&EO prediction system 180, end device 190, and VCP 410 may beimplemented as a combination of hardware and software on one or more ofdevices 900. As shown in FIG. 9, device 900 may include a bus 910, aprocessor 920, a memory 930 with software 935, an input device 940, anoutput device 950, and a communication interface 960.

Communication channel 910 may include a path that permits communicationamong the components of device 900. Processor 920 may include aprocessor, a microprocessor, or processing logic that may interpret andexecute instructions. Memory 930 may include any type of dynamic storagedevice that may store information and instructions, for execution byprocessor 920, and/or any type of non-volatile storage device that maystore information for use by processor 920.

Software 935 includes an application or a program that provides afunction and/or a process. Software 935 is also intended to includefirmware, middleware, microcode, hardware description language (HDL),and/or other form of instruction. By way of example, when device 900 isan P&EO controller 170, software 935 may include power orchestrationscenarios 350, as described herein.

Input device 940 may include a mechanism that permits a user to inputinformation to device 900, such as a keyboard, a keypad, a button, aswitch, touch screen, etc. Output device 950 may include a mechanismthat outputs information to the user, such as a display, a speaker, oneor more light emitting diodes (LEDs), etc.

Communication interface 960 may include a transceiver that enablesdevice 900 to communicate with other devices and/or systems via wirelesscommunications, wired communications, or a combination of wireless andwired communications. For example, communication interface 960 mayinclude mechanisms for communicating with another device or system via anetwork. Communication interface 960 may include an antenna assembly fortransmission and/or reception of RF signals. For example, communicationinterface 960 may include one or more antennas to transmit and/orreceive RF signals over the air. In one implementation, for example,communication interface 960 may communicate with a network and/ordevices connected to a network. Alternatively or additionally,communication interface 960 may be a logical component that includesinput and output ports, input and output systems, and/or other input andoutput components that facilitate the transmission of data to otherdevices.

Device 900 may perform certain operations in response to processor 920executing software instructions (e.g., software 935) contained in acomputer-readable medium, such as memory 930. A computer-readable mediummay be defined as a non-transitory memory device. A non-transitorymemory device may include memory space within a single physical memorydevice or spread across multiple physical memory devices. The softwareinstructions may be read into memory 930 from another computer-readablemedium or from another device. The software instructions contained inmemory 930 may cause processor 920 to perform processes describedherein. Alternatively, hardwired circuitry may be used in place of or incombination with software instructions to implement processes describedherein. Thus, implementations described herein are not limited to anyspecific combination of hardware circuitry and software.

Device 900 may include fewer components, additional components,different components, and/or differently arranged components than thoseillustrated in FIG. 9. As an example, in some implementations, a displaymay not be included in device 900. As another example, device 900 mayinclude one or more switch fabrics instead of, or in addition to, bus910. Additionally, or alternatively, one or more components of device900 may perform one or more tasks described as being performed by one ormore other components of device 900.

Systems and methods described herein provide a power and environmentalorchestration (P&EO) system that uses network utilization conditioninformation to implement scenarios that partially or fully reduce powerrequirements for radio access network (RAN) elements. A network deviceobtains power orchestration scenarios for a RAN and evaluatesutilization data of multiple components of the RAN against the powerorchestration scenarios. The network device determines that theutilization data meets a threshold for one of the power orchestrationscenarios and applies the one of the power orchestration scenarios toreconfigure the RAN for reduced power consumption.

The P&EO system described herein provides the ability to measure,predict, and control power consumption based on user demand forpredicted performance, which can reduce the cost of power use and alsoplant costs. The P&EO system may also allow networks to adapt to knownpower constraints, such as scheduled outages, brownouts, etc. In a powerfailure scenario, the P&EO system described herein also may applyreduced performance criteria to maximize battery and generator capacityuntil a service restoration. Additionally, the P&EO system may allowcertain types of traffic, such as IoT with low bandwidth, to be moved toa lower power band (such as 700 MHz) if demand is low, since the powerneeded for higher bands (such as millimeter-wave bands) can be reservedfor higher bandwidth applications.

As set forth in this description and illustrated by the drawings,reference is made to “an exemplary embodiment,” “an embodiment,”“embodiments,” etc., which may include a particular feature, structureor characteristic in connection with an embodiment(s). However, the useof the phrase or term “an embodiment,” “embodiments,” etc., in variousplaces in the specification does not necessarily refer to allembodiments described, nor does it necessarily refer to the sameembodiment, nor are separate or alternative embodiments necessarilymutually exclusive of other embodiment(s). The same applies to the term“implementation,” “implementations,” etc.

The foregoing description of embodiments provides illustration, but isnot intended to be exhaustive or to limit the embodiments to the preciseform disclosed. Accordingly, modifications to the embodiments describedherein may be possible. For example, various modifications and changesmay be made thereto, and additional embodiments may be implemented,without departing from the broader scope of the invention as set forthin the claims that follow. The description and drawings are accordinglyto be regarded as illustrative rather than restrictive.

The terms “a,” “an,” and “the” are intended to be interpreted to includeone or more items. Further, the phrase “based on” is intended to beinterpreted as “based, at least in part, on,” unless explicitly statedotherwise. The term “and/or” is intended to be interpreted to includeany and all combinations of one or more of the associated items. Theword “exemplary” is used herein to mean “serving as an example.” Anyembodiment or implementation described as “exemplary” is not necessarilyto be construed as preferred or advantageous over other embodiments orimplementations.

In addition, while series of blocks have been described with regard tothe processes illustrated in FIGS. 5 and 8, the order of the blocks maybe modified according to other embodiments. Further, non-dependentblocks may be performed in parallel. Additionally, other processesdescribed in this description may be modified and/or non-dependentoperations may be performed in parallel.

Embodiments described herein may be implemented in many different formsof software executed by hardware. For example, a process or a functionmay be implemented as “logic,” a “component,” or an “element.” Thelogic, the component, or the element, may include, for example, hardware(e.g., processor 920, etc.), or a combination of hardware and software(e.g., software 935).

Embodiments have been described without reference to the specificsoftware code because the software code can be designed to implement theembodiments based on the description herein and commercially availablesoftware design environments and/or languages. For example, varioustypes of programming languages including, for example, a compiledlanguage, an interpreted language, a declarative language, or aprocedural language may be implemented.

Use of ordinal terms such as “first,” “second,” “third,” etc., in theclaims to modify a claim element does not by itself connote anypriority, precedence, or order of one claim element over another, thetemporal order in which acts of a method are performed, the temporalorder in which instructions executed by a device are performed, etc.,but are used merely as labels to distinguish one claim element having acertain name from another element having a same name (but for use of theordinal term) to distinguish the claim elements.

Additionally, embodiments described herein may be implemented as anon-transitory computer-readable storage medium that stores data and/orinformation, such as instructions, program code, a data structure, aprogram module, an application, a script, or other known or conventionalform suitable for use in a computing environment. The program code,instructions, application, etc., is readable and executable by aprocessor (e.g., processor 920) of a device. A non-transitory storagemedium includes one or more of the storage mediums described in relationto memory 930.

To the extent the aforementioned embodiments collect, store or employpersonal information of individuals, it should be understood that suchinformation shall be collected, stored and used in accordance with allapplicable laws concerning protection of personal information.Additionally, the collection, storage and use of such information may besubject to consent of the individual to such activity, for example,through well known “opt-in” or “opt-out” processes as may be appropriatefor the situation and type of information. Storage and use of personalinformation may be in an appropriately secure manner reflective of thetype of information, for example, through various encryption andanonymization techniques for particularly sensitive information.

No element, act, or instruction set forth in this description should beconstrued as critical or essential to the embodiments described hereinunless explicitly indicated as such. All structural and functionalequivalents to the elements of the various aspects set forth in thisdisclosure that are known or later come to be known to those of ordinaryskill in the art are expressly incorporated herein by reference and areintended to be encompassed by the claims.

What is claimed is:
 1. A method, comprising: obtaining, by a networkdevice, power orchestration scenarios for a radio access network (RAN);evaluating, by the network device, utilization data of multiplecomponents of the RAN against the power orchestration scenarios;determining, by the network device, that the utilization data meets athreshold for one of the power orchestration scenarios; and applying, bythe network device, the one of the power orchestration scenarios toreconfigure the RAN for reduced power consumption.
 2. The method ofclaim 1, further comprising: determining that the utilization data nolonger meets the threshold for the one of the power orchestrationscenarios; and applying a default power orchestration scenario to returnthe RAN to normal power consumption.
 3. The method of claim 1, furthercomprising: receiving, by the network device, verification or adjustmentof the one of the power orchestration scenarios from a self-organizingnetwork (SON) function.
 4. The method of claim 1, further comprising:ingesting historical utilization data of the multiple components of theRAN; generating, based on the historical utilization data, a predictiveutilization model for the RAN; and generating one of the powerorchestration scenarios to optimize power consumption of the RAN basedon the predictive utilization model.
 5. The method of claim 1, furthercomprising: ingesting real-time utilization data; and updating, based onhistorical utilization data and the real-time utilization data, thepredictive utilization model.
 6. The method of claim 5, wherein thereal-time utilization data incudes power supply data for a generator orback-up battery.
 7. The method of claim 1, wherein each of the powerorchestration scenarios includes a different configuration for powerconsumption and service availability in the RAN.
 8. The method of claim1, wherein the one of the power orchestration scenarios reduces thenumber of active sector carriers for a cell site.
 9. The method of claim1, further comprising: retrieving the utilization data via a message busin real-time.
 10. The method of claim 1, wherein the network device isincluded within a virtualized controller platform in one of: an edge hubfor a radio access network; or a multi-access edge computing (MEC)network.
 11. A network device in an application service layer network,the network device comprising: one or more processors configured toexecute instructions to: obtain power orchestration scenarios for aradio access network (RAN); evaluate utilization data of multiplecomponents of the RAN against the power orchestration scenarios;determine that the utilization data meets a threshold for one of thepower orchestration scenarios; and apply the one of the powerorchestration scenarios to reconfigure the RAN for reduced powerconsumption.
 12. The network device of claim 11, wherein the one or moreprocessors are further configured to: determine that the utilizationdata no longer meets the threshold for the one of the powerorchestration scenarios; and apply a default power orchestrationscenario to return the RAN to normal power consumption.
 13. The networkdevice of claim 11, wherein the one or more processors are furtherconfigured to: receive verification or adjustment of the one of thepower orchestration scenarios from a self-organizing network (SON)function.
 14. The network device of claim 11, wherein the one or moreprocessors are further configured to: ingest historical utilization dataof the multiple components of the RAN; generate, based on the historicalutilization data, a predictive utilization model for the RAN; andgenerate one of the power orchestration scenarios to optimize powerconsumption of the RAN based on the predictive utilization model. 15.The network device of claim 11, wherein the one or more processors arefurther configured to: ingest real-time utilization data; and update,based on historical utilization data and the real-time utilization data,the predictive utilization model.
 16. The network device of claim 11,wherein the one of the power orchestration scenarios reduces the numberof active sector carriers for a wireless station.
 17. The network deviceof claim 11, wherein the one or more processors are further configuredto: retrieve the utilization data via a message bus in real-time
 18. Anon-transitory computer-readable storage medium storing instructionsexecutable by a processor of a device, which when executed cause thedevice to: obtain power orchestration scenarios for a radio accessnetwork (RAN); evaluate utilization data of multiple components of theRAN against the power orchestration scenarios; determine that theutilization data meets a threshold for one of the power orchestrationscenarios; and apply the one of the power orchestration scenarios toreconfigure the RAN for reduced power consumption.
 19. Thenon-transitory computer-readable storage medium of claim 18, wherein theinstructions to apply the certified timestamp further includeinstructions to: determine that the utilization data no longer meets thethreshold for the one of the power orchestration scenarios; and apply adefault power orchestration scenario to return the RAN to normal powerconsumption.
 20. The non-transitory computer-readable storage medium ofclaim 18, further comprising instructions to: send to a self-organizingnetwork (SON) function a query to implement the one of the powerorchestration scenarios; receive from the SON function a network deviceconfiguration to implement the one of the power orchestration scenarios.